DATA VISUALIZATION:
A PRIMER
Data is only as useful as our ability to understand it
Digitalization has reached every aspect of our lives. This has led to an increase in the availability of data which combined with technological advances created a revolution in the use of big data. The availability of more data has not necessarily led to greater insights because few of us are experts in sorting through massive spreadsheets of information. The sheer volume of data is overwhelming. More is needed so that people can make sense of the data and discover the meaning within the numbers. Visual representations of data seek to address this challenge.
Through the use of visualization, the stories hidden in an overwhelming sea of data become clear.
Why Visualization?
We acquire more information through vision than through all other senses combined.1 Hear a piece of information, and three days later you'll remember 10% of it. Add a picture and you'll remember 65%.2
Gathering all of the information at once via Simultaneous Processing vs. obtaining information piece by piece through sequential processing.
Information can be visualized in many ways, depending on the information itself, the story being told, the audience, and the method of delivery. These are just some of the factors that will help define the most appropriate visual representation of the data. At times, an infographic with strong visuals will best suit the narrative while a graph or a combination of graphs might be ideal for other situations. In other occasions, data visualization will allow the user to explore the dataset to its fullest.
INFOGRAPHIC
Source: Natural Resources Canada. 8 facts about Canada's boreal forest. 2017. Accessed on 18/06/2018.
GRAPH
Deforestation: 0.03 million hectares
Insect damage: 20.3 million hectares
Harvesting: 0.72 million hectares
Forest fires: 3.9 million hectares
Source: Natural Resources Canada. 2017. The State of Canada’s Forests, Annual Report 2016.
DATA VISUALIZATION
Source: Global Forest Watch. 2014. World Resources Institute. Accessed on 18/06/2018.
1 Ware, Colin. Visualization. Perception for Design. San Francisco: Elsevier, 2004. p.2. Second Edition
2 Medina, John. Visualization. Brain Rules
What is Data Visualization?
Even though the art of representing information visually is thousands of years old, the vocabulary of the field is still evolving. Here we focus on data visualization defined as an interactive visual representation of data to facilitate understanding. While data visualizations can vary greatly in complexity and aesthetics, key features include:
EXPLORABILITY:
The ability to explore multiple variables and combinations, as a pathway to uncover stories and draw insights.
ACCESSIBILITY:
A designed interface that invites discovery and does not overwhelm.
INTERACTIVITY:
A tool which allows a user to explore data and extrapolate their own findings and relations.
How a Visualization is Made
A multidisciplinary team is key for success. The ideal team to work through this process includes designers, data visualization experts, coders, subject matter experts, and coordinators. Here is an overview of how the visualization process unfolds.
1. Start with the topic
Select content
The first step is to identify a topic and consider the questions you want to ask.
2. Identify the data
Choose / prepare / organize / understand
This is a very important step and ample time should be allocated to data discovery and structuring. The better the data is understood and organized, the easier the rest of the process will be. Well-structured data is a must for visualization!
3. Design & Build
Choose basic visual model / sketch ideas / map data to visual elements / program
At this stage you might choose to use a basic visual model as a reference (e.g. bar chart, histogram, line graph). Next, you will need to map the data to visuals elements, such as position, size, colour, tone, orientation, transparency, and shape. After that comes the graphic design of the entire page and a refinement process with a focus on clarity. From the designs, the code is developed to bring the designs and interactive features to life.
4. Test and Refine
Verify accuracy / functionality / adaptability
This is a highly iterative process, particularly after the interactivity is added. This is when you will notice if a design doesn’t deliver as you expected, or the colours need to be adjusted, or you have data errors. It takes time and a great deal of team work and communication.
5. Publish
Ensure accessibility / share and distribute
Adaptations, if needed, are dictated by the web environment where the visualizations will reside. Some websites have accessibility requirements, and/or are published in multiple languages. Additional elements may include social media connections, link to downloads of data and pictures, and other explanatory elements.
6. Analyze & Revise
Receive feedback / test user patterns / revise
Once the visualization is live it is paramount to seek feedback and analyze usage data. The insights will inform future work.
Data Visualization at the Canada Energy Regulator
The Canada Energy Regulator (CER) publishes a variety of energy information and uses a number of tools to organize, structure, and share data. Tools include: infographics, charts, through to interactive visualizations using both custom development and software.
